Hongjiang Wang¹, Qingze Shen^2,*, Qin Dai¹, Yingcai Gao², Jing Gao², Tian Zhang^3,*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 625-642, 2024, DOI:10.32604/cmc.2024.051757

Abstract Deep learning has emerged in many practical applications, such as image classification, fault diagnosis, and object detection. More recently, convolutional neural networks (CNNs), representative models of deep learning, have been used to solve fault detection. However, the current design of CNNs for fault detection of wind turbine blades is highly dependent on domain knowledge and requires a large amount of trial and error. For this reason, an evolutionary YOLOv8 network has been developed to automatically find the network architecture for wind turbine blade-based fault detection. YOLOv8 is a CNN-backed object detection model. Specifically, to reduce… More >

Shaokun Liu¹, Zhiying Gao^1,2,*, Rina Su^1,2, Mengmeng Yan¹, Jianwen Wang^1,2

Energy Engineering, Vol.121, No.8, pp. 2213-2229, 2024, DOI:10.32604/ee.2024.049616

Abstract Although the aerodynamic loading of wind turbine blades under various conditions has been widely studied, the radial distribution of load along the blade under various yaw conditions and with blade flapping phenomena is poorly understood. This study aims to investigate the effects of second-order flapwise vibration on the mean and fluctuation characteristics of the torque and axial thrust of wind turbines under yaw conditions using computational fluid dynamics (CFD). In the CFD model, the blades are segmented radially to comprehensively analyze the distribution patterns of torque, axial load, and tangential load. The following results are… More >

Jicai Guo^1,2, Xiaowen Song^1,2,*, Chang Liu^1,2, Yanfeng Zhang^1,2, Shijie Guo^1,2, Jianxin Wu^1,2, Chang Cai³, Qing’an Li^3,*

Energy Engineering, Vol.121, No.7, pp. 1739-1758, 2024, DOI:10.32604/ee.2024.048854

Abstract In winter, wind turbines are susceptible to blade icing, which results in a series of energy losses and safe operation problems. Therefore, blade icing detection has become a top priority. Conventional methods primarily rely on sensor monitoring, which is expensive and has limited applications. Data-driven blade icing detection methods have become feasible with the development of artificial intelligence. However, the data-driven method is plagued by limited training samples and icing samples; therefore, this paper proposes an icing warning strategy based on the combination of feature selection (FS), eXtreme Gradient Boosting (XGBoost) algorithm, and exponentially weighted… More >

Haixia Kou^1,*, Bowen Yang¹, Xuyao Zhang², Xiaobo Yang¹, Haibo Zhao¹

Structural Durability & Health Monitoring, Vol.18, No.3, pp. 277-297, 2024, DOI:10.32604/sdhm.2024.045023

Abstract Given the difficulty in accurately evaluating the fatigue performance of large composite wind turbine blades (referred to as blades), this paper takes the main beam structure of the blade with a rectangular cross-section as the simulation object and establishes a composite laminate rectangular beam structure that simultaneously includes the flange, web, and adhesive layer, referred to as the blade main beam sub-structure specimen, through the definition of blade sub-structures. This paper examines the progressive damage evolution law of the composite laminate rectangular beam utilizing an improved 3D Hashin failure criterion, cohesive zone model, B-K failure More > Graphic Abstract

Hongsheng Su, Lixia Dong^*, Xiaoying Yu, Kai Liu

Energy Engineering, Vol.121, No.4, pp. 973-986, 2024, DOI:10.32604/ee.2023.043497

Abstract Time based maintenance (TBM) and condition based maintenance (CBM) are widely applied in many large wind farms to optimize the maintenance issues of wind turbine gearboxes, however, these maintenance strategies do not take into account environmental benefits during full life cycle such as carbon emissions issues. Hence, this article proposes a carbon emissions computing model for preventive maintenance activities of wind turbine gearboxes to solve the issue. Based on the change of the gearbox state during operation and the influence of external random factors on the gearbox state, a stochastic differential equation model (SDE) and More > Graphic Abstract

Vasishta Bhargava Nukala^*, Chinmaya Prasad Padhy

Sound & Vibration, Vol.58, pp. 133-150, 2024, DOI:10.32604/sv.2024.047762

Abstract A significant aerodynamic noise from wind turbines arises when the rotating blades interact with turbulent flows. Though the trailing edge of the blade is an important source of noise at high frequencies, the present work deals with the influence of turbulence distortion on leading edge noise from wind turbine blades which becomes significant in low-frequency regions. Four quasi-empirical methods are studied to verify the accuracy of turbulent inflow noise predicted at low frequencies for a 2 MW horizontal axis wind turbine. Results have shown that all methods exhibited a downward linear trend in noise spectra More >

Qifa Lang, Yuqiao Zheng^*, Tiancai Cui, Chenglong Shi, Heyu Zhang

Energy Engineering, Vol.121, No.2, pp. 483-498, 2024, DOI:10.32604/ee.2023.042437

Abstract This work presents a novel approach to achieve nonlinear vibration response based on the Hamilton principle. We chose the 5-MW reference wind turbine which was established by the National Renewable Energy Laboratory (NREL), to research the effects of the nonlinear flap-wise vibration characteristics. The turbine wheel is simplified by treating the blade of a wind turbine as an Euler-Bernoulli beam, and the nonlinear flap-wise vibration characteristics of the wind turbine blades are discussed based on the simplification first. Then, the blade’s large-deflection flap-wise vibration governing equation is established by considering the nonlinear term involving the… More >

Zhoujie Zhu¹, Gang Wang¹, Qingquan Liu¹, Guojun Wang², Rui Dong², Dayong Zhang^2,3,*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.3, pp. 625-639, 2024, DOI:10.32604/fdmp.2023.042128

Abstract Important challenges must be addressed to make wind turbines sustainable renewable energy sources. A typical problem concerns the design of the foundation. If the pile diameter is larger than that of the jacket platform, traditional mechanical models cannot be used. In this study, relying on the seabed soil data of an offshore wind farm, the m-method and the equivalent embedded method are used to address the single-pile wind turbine foundation problem for different pile diameters. An approach to determine the equivalent pile length is also proposed accordingly. The results provide evidence for the effectiveness and reliability More >

Yuanjun Dai^1,2,*, Xin Wei¹, Baohua Li¹, Cong Wang¹, Kunju Shi¹

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.2, pp. 337-348, 2024, DOI:10.32604/fdmp.2023.042434

Abstract To study the impact of the trailing-edge wear on the vibrational behavior of wind-turbine blades, unworn blades and trailing-edge worn blades have been assessed through relevant modal tests. According to these experiments, the natural frequencies of trailing-edge worn blades −1, −2, and −3 increase the most in the second to fourth order, the fifth order increases in the middle, and the first order increases the least. The damping ratio data indicate that, in general, the first five-order damping ratios of trailing-edge worn blades −1 and trailing-edge worn blades −2 are reduced, and the first five-order More >

Wenyang Tang^1,2, Cong Liu^1,*, Bo Zhang²

Energy Engineering, Vol.120, No.11, pp. 2667-2681, 2023, DOI:10.32604/ee.2023.040743

Abstract Harsh working environments and wear between blades and other unit components can easily lead to cracks and damage on wind turbine blades. The cracks on the blades can endanger the shafting of the generator set, the tower and other components, and even cause the tower to collapse. To achieve high-precision wind blade crack detection, this paper proposes a crack fault-detection strategy that integrates Gated Residual Network (GRN), a fusion module and Transformer. Firstly, GRN can reduce unnecessary noisy inputs that could negatively impact performance while preserving the integrity of feature information. In addition, to gain… More >